3 10 29 https://repository.horizon.ac.id/files/original/a6a6761b968f40608dfae4fdfe5172a1.pdf bac8e41f542d0695699b202ab3642273 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Tree Algorithm Model on Size Classification Data Mining Subject The topic of the resource classification; data mining; decision tree Description An account of the resource The goal of this research is to use a tree algorithm to categorize student clothing in order to acquire an accurate size. This research is qualitative approach through descriptive analysis, while the analysis employed C.45 Tree algorithm classification. Manual calculations utilizing the tree algorithm formula revealed that the majority of students require XL-sized clothing. On the X5 (Shoulder length) characteristic, the maximum entropy and information gain values were obtained at 0.212642462. According to the forecast, the shoulder length attribute is the first calculation in developing a decision tree scheme since it has the largest entropy and information gain value. Lastly, the findings of this study analysis can be used as a mapping prediction to make decisions on the size of the student group's clothing Creator An entity primarily responsible for making the resource Agis Abhi Rafdhi, Eddy Soeryanto Soegoto, Senny Luckyardi, Chepi Nur Albar Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text classification data mining Decision Tree https://repository.horizon.ac.id/files/original/42f7e65888cbfda17db578b331f081f1.pdf 0e90fb49fc7409f7eb659d05fc954d51 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Systematic Mapping Study: Research Opportunities on Capacity Planning Subject The topic of the resource capacity planning; review; systematic mapping study Description An account of the resource The central idea of the research is to enhance the efficiency and sustainability of data centers by implementing accurate capacity planning, which will also improve their performance and availability. Various literature reviews have been conducted to understand the current status of capacity planning implementation across different domains and perspectives. However, a more organized and systematic approach is required to map research and implementation outcomes in the relevant areas of capacity planning that have the potential for further development. The present study is aimed at filling this gap by conducting a systematic mapping study, which combines both quantitative and qualitative methodologies. The quantitative approach involved the collection of literature and topic classification using the Latent Dirichlet Allocation (LDA) method. In contrast, the qualitative approach utilized content analysis to identify future research directions based on keyword trends and topics. The PRISMA framework was followed to guide the search for relevant studies in electronic research literature databases. The mapping results revealed 15 topics, with topics 8, 10, 11, and 15 showing significant potential for further research and exhibiting increasing trends. The identified topics encompass capacity planning, energy and resource management, computing and technology, data analysis and statistics, engineering, and industry, all crucial for businesses and industries to operate efficiently and sustainably. This study provides a comprehensive overview of the state of capacity planning implementation and highlights areas that require further investigation. Creator An entity primarily responsible for making the resource Yuggo Afrianto, Rendy Munadi, Setyorini, Arief Goeritno Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Capacity planning Review systematic mapping study https://repository.horizon.ac.id/files/original/fef97bd31df15ca7edcff83996ea7789.pdf e9f4b1887bb1204c9c7e39f0aaa9a120 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Implementation of Enhanced Spray Routing Protocol for VDTN On Surabaya Smart City Scenario Subject The topic of the resource smart city; vehicle delay tolerant network; surabaya; SNHD; routing protocol Description An account of the resource The application of smart-city, which promises better city management in helping to improve people's quality of life, is still inhibited due to the high cost of infrastructure investment. In several Smart cities, it takes at least $ 30 - 40 billion to convert a conventional town into a smart city, Include for Data collection infrastructure, i.e., cellular data subscription and WiFi Infrastructure. Alternatively, low-power wide-area networks (LPWAN) could be considered, but it needs more bandwidth to serve data transmission in a smart city. Vehicle Delay Tolerant Network (VDTN) is one part of DTN that employs vehicles as a communication infrastructure that allows communication in challenging conditions and could make it an alternative network for Data Collection in Smart City. This paper proposes a Surabaya Smart City scenario with VDTN as a data collection. The scenario consists of 40 wireless sensors and 50 to 200 vehicles (car and bus) with 5 Road Side Units that forward data from the sensor to the monitoring server. Furthermore, to increase the VDTN performance, we improve our proposed routing protocol, Spray and Hop Distance (SNHD), with two sprays method (Adaptive and Simple) and multiple sources and destinations data collection support. The evaluation was done by simulation-based comparison with an increase in the number of vehicles to determine the impact of vehicle density on data collection performance in terms of delivery probability, Latency Average, and Overhead Ratio. Based on the simulation results, the simple spray method in SNHD and A-SNHD outperformed the well-known VDTN routing protocol, i.e., Epidemic and Spray and Wait. Moreover, when the number of cars is increased from 50 to 200, the performance of VDTN does not increase significantly as network density increases. It means that VDTN only requires a small number of vehicles for use as a low-cost alternative network for smart city. We also evaluate the impact of data size on the performance of all routing protocols in general Creator An entity primarily responsible for making the resource Agussalim, Agung Brastama Putra Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource Pdf Language A language of the resource English Type The nature or genre of the resource Text Routing protocol Smart city SNHD surabaya vehicle delay tolerant network https://repository.horizon.ac.id/files/original/d8f2b754b5b818b6f3c446344aef68b4.pdf a5c4fb35caf3957da1da77d224a4a3ce Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Application of Object Mask Detection Using the Convolution Neural Network (CNN) Subject The topic of the resource covid-19; object detection; image processing; convolution neural network (CNN); public services Description An account of the resource The spread of Coronavirus Disease (Covid-19) is still a serious problem we are currently facing. The spread occurred very quickly through the process of face-to-face interaction. The process of face-to-face interaction that occurs both in public spaces and closed spaces has a great risk of transmitting the Covid-19 virus. One of the efforts to deal with the spread of the Covid- 19 virus is by increasing the use of masks both in public and closed spaces. Based on this, this study aims to develop an Object Detection process in image processing techniques. Object Detection development using the Convolution Neural Network (CNN) method to provide optimal output. The CNN can process the input image which is converted into a pixel matrix and then forwarded to the convolution layer. The research dataset consists of 2000 images of face masks and not masks. The images were obtained from the open sources github.com and kaggle.com. The results of the study present a system capable of detecting masks in real time. CNN provides very good performance with an accuracy rate of 99.05%. With these results, the contribution of this research can be used for the process of monitoring public services for the community to increase the use of masks. Creator An entity primarily responsible for making the resource Yuhandri, Musli Yanto, Eka Naufaldi Novri Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text convolution neural network (CNN) COVID-19 image processing Object detection public services https://repository.horizon.ac.id/files/original/ebb9d009785c5b449c69847342a9dd14.pdf 537d841ffa3d3544dae90f8deb4ae3c3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource The Joint Channel Coding and Pre-Distortion Technique on the USRP�Based MIMO-OFDM System Subject The topic of the resource MIMO; OFDM; convolutional coding; USRP; pre-distortion Description An account of the resource Modern wireless communication systems use Orthogonal Frequency Division Multiplexing (OFDM), a multi-carrier modulation method that resists multipath channels and provides bandwidth efficiency. OFDM is generally used with a Multiple�Input Multiple-Output (MIMO) system to boost diversity gain and channel capacity. MIMO-OFDM has several advantages, but its high PAPR value is a drawback. A non-linear high-power amplifier (HPA) can distort signals with high PAPR values. This issue can be resolved by employing pre-distortion (PD), which compensates for non-linear HPA. In addition to PD, channel coding can be used to improve the quality of systems with high PAPR values by adding redundant bits to the bits to be sent. In this paper, we report the experimental evaluations of the joint channel coding and pre-distortion (PD) technique on a 2x2 MIMO OFDM system using USRP hardware. The experiments are conducted in two scenarios: line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. The channel coding that is used in this scenario is convolutional code with code rates of 1/2, 2/3, and 3/4. From the experiment results, it can be seen that the system using PD combined with the convolution code produces better performance in LOS and NLOS scenarios compared to the system without PD. In the LOS scenario, the use of PD can improve the SNR value of code rates 1/2, 2/3, and 3/4 by about 58.74%, 75.97%, and 96.20%. In the NLOS scenario, the use of PD can improve the SNR value of code rates 1/2, 2/3, and 3/4 by about 60.71%, 73.59%, and 71.84%. The LOS scenario measurement gives a better SNR value than the NLOS scenario, with a maximum SNR value of 30.86 dB, while the NLOS scenario maximum SNR value is 30.23 dB. This happened because the LOS scenario suffered minimal multipath fading compared to the NLOS scenario Creator An entity primarily responsible for making the resource Melki Mario Gulo, I Gede Puja Astawa, Arifin, Yoedy Moegiharto, Hendy Briantoro Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text convolutional coding MIMO OFDM pre-distortion USRP https://repository.horizon.ac.id/files/original/4156705703dfad4a4e949ec06ab2086a.pdf 48a310c8b5d28cea5f10060ee57a4d32 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Performance Comparison of Convolutional Neural Network and MobileNetV2 for Chili Diseases Classification Subject The topic of the resource chili; comparison; CNN; mobilenetV2 Description An account of the resource Chili is an important agricultural commodity in Indonesia and plays a significant role in the nation's economic growth. Its demand by households and industries reaches up to 61%. However, this high demand also means that monitoring efforts need to be intensified, particularly for chili plant diseases that can greatly impact yields. If these diseases are not promptly addressed, they can lead to a decrease in production levels, which can negatively affect the economy. With technological advancements, automatic monitoring using image processing is now highly feasible, making monitoring more efficient and effective. Common chili plant diseases include Chili leaf yellowing disease, Chili leaf curling disease, and cercospora leaf spots and Magnesium Deficiency with symptoms that can be observed through the shape and color of the leaves. This research aims to classify chili plant diseases by comparing the CNN algorithm and the pre-trained MobileNetV2 based model performance using Confussion Matrix. The study shows that the MobileNetV2 model, trained with a learning rate of 0.001, produces a more optimal model with an accuracy of 90% and based on the calculation of the confusion matrix, the average percentage values for recall, precision, and F1 score are 92%. These findings highlight the potential of image processing and pre-trained models to support efforts to monitor plant diseases and improve chili production. Creator An entity primarily responsible for making the resource Achmad Naila Muna Ramadhani, Galuh Wilujeng Saraswati, Rama Tri Agung, Heru Agus Santoso Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text chili CNN Comparison MobileNetV2 https://repository.horizon.ac.id/files/original/71fa622c6288b9d83fe8fbc78e751cdd.pdf de14e35e6e967cd0602d949d5ef23c75 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Classification of Acute Lymphoblastic Leukemia based on White Blood Cell Images using InceptionV3 Model Subject The topic of the resource ALL; CNN; deep learning; inceptionV3; leukemia Description An account of the resource Acute Lymphoblastic Leukemia (ALL) is the most prevalent form of leukemia that occurs in children. Detection of ALL through white blood cell image analysis can assist in prognosis and appropriate treatment. In this study, the author proposes an approach for classifying ALL based on white blood cell images using a Convolutional Neural Network (CNN) model called InceptionV3. The dataset used in this research consists of white blood cell images collected from patients with ALL and healthy individuals. These images were obtained from The Cancer Imaging Archive (TCIA), which is a service for storing large-scale cancer medical images available to the public. During the evaluation phase, the author used training data evaluation metrics such as accuracy and loss to measure the model's performance. The research results show that the InceptionV3 model is capable of classifying white blood cell images with a high level of accuracy. This model achieves an average ALL recognition accuracy of 0.9896 with a loss of 0.031. The use of CNN models like InceptionV3 in medical image analysis has the potential to enhance the efficiency and accuracy of image-based disease diagnosis Creator An entity primarily responsible for making the resource Rizki Firdaus Mulya, Ema Utami, Dhani Ariatmanto Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text ALL CNN deep learning InceptionV3 Leukemia https://repository.horizon.ac.id/files/original/d8f5fe8a03009ce9203320c76743c7ec.pdf 3ded903ef0f07e57c8a3a479001bc46a Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Brent Crude Oil Price Forecasting using the Cascade Forward Neural Network Subject The topic of the resource artificial neural networks; cascade forwards; brent; crude oil; MAPE Description An account of the resource Crude oil is one of the most traded non-food products or commodities in the world. In Indonesia, crude oil will still be a contributor to the Gross Domestic Product in 2021. Excessive consumption of fuel oil (BBM) in Indonesia has resulted in a scarcity of crude oil, especially diesel. Forecasting the price of Brent crude oil is an important effort to anticipate fluctuations in the price of fuel oil. The Cascade Forward Neural Network (CFNN) method is proposed to forecast fuel prices because of its superiority in fluctuating data types. The data used in this research is the price of Brent crude oil in the period January 2008 to December 2022. The CFNN method will be evaluated using the Mean Absolute Percentage Error (MAPE) to choose the best architectural model. The best Architectural Model is used to predict the next 12 months. After 10 architectural model trials, 2-6-1 became the best model with a MAPE data training value of 6.3473% and MAPE data testing of 9.4689%. Forecasting results for Brent crude oil for the next 12 months tend to experience a downward trend until December 2023. Creator An entity primarily responsible for making the resource Fatkhurokhman Fauzi, Dewi Ratnasari Wijaya, Tiani Wahyu Utami Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text Artificial neural networks brent cascade forwards crude oil MAPE https://repository.horizon.ac.id/files/original/71ee181ad62792f159b87dbb4b7959e6.pdf beb45f445151b24d3e22e56d15c6539b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 7 NO 4 (2023) Contributor An entity responsible for making contributions to the resource Sri Wahyuni Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Exploring Research Trends and Impact: A Bibliometric Analysis of RESTI Journal from 2018 to 2022 Subject The topic of the resource bibliometric; dimensions; journal; RESTI; research trends Description An account of the resource This study provides a comprehensive analysis of the RESTI Journal, a prominent publication in the field of systems engineering and information technology. The analysis aims to evaluate the journal's publication output, citation impact, and overall contribution to the field. The study uses data from the Dimensions database, focusing on articles published between 2018 and 2022, resulting in a data set of 594 articles. To analyze the data collected, the study employs bibliometric and network visualization tools such as Bibliometrix and VOSviewer. The analysis reveals a notable increase in the number of publications over time, indicating a growing interest and research activity in the field. Furthermore, the distribution of author productivity deviates from Lotka's law, highlighting variations in author patterns and productivity levels. An examination of institutional affiliations reveals Telkom University as the dominant institution, making a substantial contribution to the journal. Visualizations based on author-provided titles, abstracts, and keywords highlight research trends in image recognition and classification, with a particular emphasis on utilizing convolutional neural networks (CNN) and Support Vector Machines (SVM). Overall, this study provides valuable information on the performance and trends of the RESTI Journal. The findings contribute to a deeper understanding of the impact and its role in advancing knowledge in systems engineering and information technology. These insights can inform researchers, practitioners, and stakeholders in the field, guide future research directions and improve the scholarly impact of the RESTI Journal. Creator An entity primarily responsible for making the resource Ronal Watrianthos, Yuhefizar Source A related resource from which the described resource is derived http://jurnal.iaii.or.id Publisher An entity responsible for making the resource available Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association Date A point or period of time associated with an event in the lifecycle of the resource August 2023 Contributor An entity responsible for making contributions to the resource Sri Wahyuni Rights Information about rights held in and over the resource ISSN Media Electronic: 2580-0760 Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource English Type The nature or genre of the resource Text bibliometric; Dimensions Journal research trends RESTI